993 resultados para Particle tracking detectors


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La determinación experimental in situ del escurrimiento superficial en cauces naturales (mediante aforos) en forma sistemática permite lograr una mayor eficiencia en la gestión del recurso hídrico en una cuenca determinada. Además, la determinación precisa de los caudales es relevante para el diseño sustentable de infraestructura hídrica (puentes, canalizaciones, etc.) debido en parte a que el sobredimensionamiento de las obras genera un impacto innecesario sobre el medio ambiente, además de que resulta antieconómico. Además, la subestimación de las obras a diseñar provoca fallos con resultados catastróficos con alto impacto sobre la sociedad y el medio ambiente, ya sea por la pérdida de vidas humanas como de bienes públicos y privados. En los últimos años se ha incrementado el instrumental disponible para la cuantificación experimental de caudales de agua superficial en cauces naturales con tecnología que permite caracterizar el flujo de agua con mayor resolución espacial y temporal. Específicamente, el empleo de la anemometría acústica basada en el efecto Doppler (que utiliza el principio físico del cambio de frecuencia ante el rebote acústico que produce una partícula transportada por el flujo) se ha tornado actualmente una práctica universal en hidráulica fluvial y está reemplazando a las metodologías convencionales como por ejemplo el uso de molinetes. El instrumento acústico utilizado comúnmente en el caso de mediciones en campo, es el ADCP (Acoustic Doppler Current Profiler). Por otra parte desde hace algunos años se están desarrollando metodologías experimentales que permiten medir el campo de velocidades del flujo en manera instantánea y con alta resolución espacial mediante el procesamiento digital de imágenes. Dentro de estos métodos se destaca el de velocimetría por seguimiento de partículas PTV (Particle Tracking Velocimetry) de reciente aplicación a nivel mundial en mediciones de campo. Sobre esta base, se considera un desafío tecnológico la implementación en nuestra provincia de estas modernas tecnologías, ya validadas en el ámbito de la Universidad Nacional de Córdoba para la obtención precisa de registros de caudales en cauces naturales. Mediante este proyecto de transferencia de los resultados de investigación y comunicación pública de la ciencia, el grupo de Investigación del CETA - FCEFyN -UNC realizará un "Programa de capacitación y actualización en modernas técnicas experimentales para medición de caudales de aguas superficiales en cauces naturales" que incluye los recientes avances observados en la temática. La Secretaría de Recursos Hídricos del Ministerio de Agua, Ambiente y Energía de la Provincia de Córdoba será beneficiada y se fortalecerá en una de sus principales funciones que es: "procurar el fortalecimiento de redes de mediciones o monitoreo sistemático a través de programas de cooperación técnica y presupuestaria con entidades provinciales y nacionales -públicas o privadas-, prestatarias de obras y servicios públicos y los usuarios del agua, manteniendo un sistema de información provincial sobre las variables meteorológicas y el recurso hídrico con el objeto de procesar su flujo en forma permanente".

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Particle flow patterns were investigated for wet granulation and dry powder mixing in ploughshare mixers using Positron Emission Particle Tracking (PEPT). In a 4-1 mixer, calcium carbonate with mean size 45 mum was granulated using a 50 wt.% solution of glycerol and water as binding fluid, and particle movement was followed using a 600-mum calcium hydroxy-phosphate tracer particle. In a 20-1 mixer, dry powder flow was studied using a 600-mum resin bead tracer particle to simulate the bulk polypropylene powder with mean size 600 mum. Important differences were seen between particle flow patterns for wet and dry systems. Particle speed relative to blade speed was lower in the wet system than in the dry system, with the ratios of average particle speed to blade tip speed for all experiments in the range 0.01-015. In the axial plane, the same particle motion was observed around each blade; this provides a significant advance for modelling flow in ploughshare mixers. For the future, a detailed understanding of the local velocity, acceleration and density variations around a plough blade will reveal the effects of flow patterns in granulating systems on the resultant distribution of granular product attributes such as size, density and strength. (C) 2002 Elsevier Science B.V All rights reserved.

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The plasma membrane is a complex, dynamic structure that provides platforms for the assembly of many signal transduction pathways. These platforms have the capacity to impose an additional level of regulation on cell signalling networks. In this review, we will consider specifically how Ras proteins interact with the plasma membrane. The focus will be on recent studies that provide novel spatial and dynamic insights into the micro-environments that different Ras proteins utilize for signal transduction. We will correlate these recent studies suggesting Ras proteins might operate within a heterogeneous plasma membrane with earlier biochemical work on Ras signal transduction.

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The article deals with the CFD modelling of fast pyrolysis of biomass in an Entrained Flow Reactor (EFR). The Lagrangian approach is adopted for the particle tracking, while the flow of the inert gas is treated with the standard Eulerian method for gases. The model includes the thermal degradation of biomass to char with simultaneous evolution of gases and tars from a discrete biomass particle. The chemical reactions are represented using a two-stage, semi-global model. The radial distribution of the pyrolysis products is predicted as well as their effect on the particle properties. The convective heat transfer to the surface of the particle is computed using the Ranz-Marshall correlation.

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Computational Fluid Dynamics (CFD) has found great acceptance among the engineering community as a tool for research and design of processes that are practically difficult or expensive to study experimentally. One of these processes is the biomass gasification in a Circulating Fluidized Bed (CFB). Biomass gasification is the thermo-chemical conversion of biomass at a high temperature and a controlled oxygen amount into fuel gas, also sometime referred to as syngas. Circulating fluidized bed is a type of reactor in which it is possible to maintain a stable and continuous circulation of solids in a gas-solid system. The main objectives of this thesis are four folds: (i) Develop a three-dimensional predictive model of biomass gasification in a CFB riser using advanced Computational Fluid Dynamic (CFD) (ii) Experimentally validate the developed hydrodynamic model using conventional and advanced measuring techniques (iii) Study the complex hydrodynamics, heat transfer and reaction kinetics through modelling and simulation (iv) Study the CFB gasifier performance through parametric analysis and identify the optimum operating condition to maximize the product gas quality. Two different and complimentary experimental techniques were used to validate the hydrodynamic model, namely pressure measurement and particle tracking. The pressure measurement is a very common and widely used technique in fluidized bed studies, while, particle tracking using PEPT, which was originally developed for medical imaging, is a relatively new technique in the engineering field. It is relatively expensive and only available at few research centres around the world. This study started with a simple poly-dispersed single solid phase then moved to binary solid phases. The single solid phase was used for primary validations and eliminating unnecessary options and steps in building the hydrodynamic model. Then the outcomes from the primary validations were applied to the secondary validations of the binary mixture to avoid time consuming computations. Studies on binary solid mixture hydrodynamics is rarely reported in the literature. In this study the binary solid mixture was modelled and validated using experimental data from the both techniques mentioned above. Good agreement was achieved with the both techniques. According to the general gasification steps the developed model has been separated into three main gasification stages; drying, devolatilization and tar cracking, and partial combustion and gasification. The drying was modelled as a mass transfer from the solid phase to the gas phase. The devolatilization and tar cracking model consist of two steps; the devolatilization of the biomass which is used as a single reaction to generate the biomass gases from the volatile materials and tar cracking. The latter is also modelled as one reaction to generate gases with fixed mass fractions. The first reaction was classified as a heterogeneous reaction while the second reaction was classified as homogenous reaction. The partial combustion and gasification model consisted of carbon combustion reactions and carbon and gas phase reactions. The partial combustion considered was for C, CO, H2 and CH4. The carbon gasification reactions used in this study is the Boudouard reaction with CO2, the reaction with H2O and Methanation (Methane forming reaction) reaction to generate methane. The other gas phase reactions considered in this study are the water gas shift reaction, which is modelled as a reversible reaction and the methane steam reforming reaction. The developed gasification model was validated using different experimental data from the literature and for a wide range of operating conditions. Good agreement was observed, thus confirming the capability of the model in predicting biomass gasification in a CFB to a great accuracy. The developed model has been successfully used to carry out sensitivity and parametric analysis. The sensitivity analysis included: study of the effect of inclusion of various combustion reaction; and the effect of radiation in the gasification reaction. The developed model was also used to carry out parametric analysis by changing the following gasifier operating conditions: fuel/air ratio; biomass flow rates; sand (heat carrier) temperatures; sand flow rates; sand and biomass particle sizes; gasifying agent (pure air or pure steam); pyrolysis models used; steam/biomass ratio. Finally, based on these parametric and sensitivity analysis a final model was recommended for the simulation of biomass gasification in a CFB riser.

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We thank Frans Bianchi and Franz Ho for assistance with molecular cloning, Tim Rasmussen for providing the pTRC-MscK plasmid, Andrew Robinson for providing the pBAD-mEos3.2 plasmid, Matthias Heinemann for assistance with the flow cytometry measurements, Paul Schavemaker for performing Smoldyn simulations and Michiel Punter for programming ImageJ plugins for PALM reconstructions and single-particle tracking. We thank Ian Booth for critical reading of the manuscript, and Christoffer Åberg and Matteo Gabba for valuable discussions. The authors would like to thank David Dryden and Marcel Reuter for performing preliminary experiments from which this work has been built. The work was funded by the EU FP7 ITN-network program NICHE.

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An Euler-Lagrange particle tracking model, developed for simulating fire atmosphere/sprinkler spray interactions, is described. Full details of the model along with the approximations made and restrictions applying are presented. Errors commonly found in previous formulations of the source terms used in this two-phase approach are described and corrected. In order to demonstrate the capabilities of the model it is applied to the simulation of a fire in a long corridor containing a sprinkler. The simulation presented is three-dimensional and transient and considers mass, momentum and energy transfer between the gaseous atmosphere and injected liquid droplets.

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An integrated method for the prediction of the spatial pollution distribution within a street canyon directly from a microscopic traffic simulation model is outlined. The traffic simulation package Paramics is used to model the flow of vehicles in realistic traffic conditions on a real road network. This produces details of the amount of pollutant produced by each vehicle at any given time. The authors calculate the dispersion of the pollutant using a particle tracking diffusion method which is superimposed on a known velocity and turbulence field. This paper shows how these individual components may be integrated to provide a practical street canyon pollution model. The resulting street canyon pollution model provides isoconcentrations of pollutant within the road topography.

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Recent developments have made researchers to reconsider Lagrangian measurement techniques as an alternative to their Eulerian counterpart when investigating non-stationary flows. This thesis advances the state-of-the-art of Lagrangian measurement techniques by pursuing three different objectives: (i) developing new Lagrangian measurement techniques for difficult-to-measure, in situ flow environments; (ii) developing new post-processing strategies designed for unstructured Lagrangian data, as well as providing guidelines towards their use; and (iii) presenting the advantages that the Lagrangian framework has over their Eulerian counterpart in various non-stationary flow problems. Towards the first objective, a large-scale particle tracking velocimetry apparatus is designed for atmospheric surface layer measurements. Towards the second objective, two techniques, one for identifying Lagrangian Coherent Structures (LCS) and the other for characterizing entrainment directly from unstructured Lagrangian data, are developed. Finally, towards the third objective, the advantages of Lagrangian-based measurements are showcased in two unsteady flow problems: the atmospheric surface layer, and entrainment in a non-stationary turbulent flow. Through developing new experimental and post-processing strategies for Lagrangian data, and through showcasing the advantages of Lagrangian data in various non-stationary flows, the thesis works to help investigators to more easily adopt Lagrangian-based measurement techniques.

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During the last decade advances in the field of sensor design and improved base materials have pushed the radiation hardness of the current silicon detector technology to impressive performance. It should allow operation of the tracking systems of the Large Hadron Collider (LHC) experiments at nominal luminosity (1034 cm-2s-1) for about 10 years. The current silicon detectors are unable to cope with such an environment. Silicon carbide (SiC), which has recently been recognized as potentially radiation hard, is now studied. In this work it was analyzed the effect of high energy neutron irradiation on 4H-SiC particle detectors. Schottky and junction particle detectors were irradiated with 1 MeV neutrons up to fluence of 1016 cm-2. It is well known that the degradation of the detectors with irradiation, independently of the structure used for their realization, is caused by lattice defects, like creation of point-like defect, dopant deactivation and dead layer formation and that a crucial aspect for the understanding of the defect kinetics at a microscopic level is the correct identification of the crystal defects in terms of their electrical activity. In order to clarify the defect kinetic it were carried out a thermal transient spectroscopy (DLTS and PICTS) analysis of different samples irradiated at increasing fluences. The defect evolution was correlated with the transport properties of the irradiated detector, always comparing with the un-irradiated one. The charge collection efficiency degradation of Schottky detectors induced by neutron irradiation was related to the increasing concentration of defects as function of the neutron fluence.

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This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

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Silicon particle detectors are used in several applications and will clearly require better hardness against particle radiation in the future large scale experiments than can be provided today. To achieve this goal, more irradiation studies with defect generating bombarding particles are needed. Protons can be considered as important bombarding species, although neutrons and electrons are perhaps the most widely used particles in such irradiation studies. Protons provide unique possibilities, as their defect production rates are clearly higher than those of neutrons and electrons, and, their damage creation in silicon is most similar to the that of pions. This thesis explores the development and testing of an irradiation facility that provides the cooling of the detector and on-line electrical characterisation, such as current-voltage (IV) and capacitance-voltage (CV) measurements. This irradiation facility, which employs a 5-MV tandem accelerator, appears to function well, but some disadvantageous limitations are related to MeV-proton irradiation of silicon particle detectors. Typically, detectors are in non-operational mode during irradiation (i.e., without the applied bias voltage). However, in real experiments the detectors are biased; the ionising proton generates electron-hole pairs, and a rise in rate of proton flux may cause the detector to breakdown. This limits the proton flux for the irradiation of biased detectors. In this work, it is shown that, if detectors are irradiated and kept operational, the electric field decreases the introduction rate of negative space-charges and current-related damage. The effects of various particles with different energies are scaled to each others by the non-ionising energy loss (NIEL) hypothesis. The type of defects induced by irradiation depends on the energy used, and this thesis also discusses the minimum proton energy required at which the NIEL-scaling is valid.

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Standard algorithms in tracking and other state-space models assume identical and synchronous sampling rates for the state and measurement processes. However, real trajectories of objects are typically characterized by prolonged smooth sections, with sharp, but infrequent, changes. Thus, a more parsimonious representation of a target trajectory may be obtained by direct modeling of maneuver times in the state process, independently from the observation times. This is achieved by assuming the state arrival times to follow a random process, typically specified as Markovian, so that state points may be allocated along the trajectory according to the degree of variation observed. The resulting variable dimension state inference problem is solved by developing an efficient variable rate particle filtering algorithm to recursively update the posterior distribution of the state sequence as new data becomes available. The methodology is quite general and can be applied across many models where dynamic model uncertainty occurs on-line. Specific models are proposed for the dynamics of a moving object under internal forcing, expressed in terms of the intrinsic dynamics of the object. The performance of the algorithms with these dynamical models is demonstrated on several challenging maneuvering target tracking problems in clutter. © 2006 IEEE.